Research partnership to use iPhone biometrics to detect depression and cognitive decline


Apple is collaborating with the University of California at Los Angeles (UCLA) and Biogen on new biometric capabilities for iPhones aimed at detecting depression and signs of cognitive decline via expression recognition and behavioral biometrics.

The collaboration was revealed by The Wall Street Journal, which reportedly learned about it after speaking to people familiar with the matter and reading documents related to the project.

The new technology would collect physiological data from users from a variety of sensors, and would include mobility, physical activity, sleep patterns, typing behavior, etc.

By simultaneously monitoring this biometric information, researchers attempt to pinpoint digital signals associated with target conditions so that reliable algorithms can be created to consistently detect them.

The data collected from the new tests will be compared to standard brain health tests, including traditional cognitive assessments and scans that track plaque buildup in the brain.

If found to be effective at detecting early signs of cognitive decline, the biometric technology can then be incorporated into new iPhone models, potentially dealing with rising rates of depression and anxiety as well as other brain disorders.

Apple has yet to confirm whether the technology will actually be applied to its devices, as it is still in an experimental stage.

However, the Cupertino-based company has stepped up its healthcare efforts in recent years, suggesting it will continue to explore technology in the space.

In fact, this isn’t the first biometric health monitoring collaboration between Apple and Biogen, with a similar collaboration unveiled in January of this year.

According to new documents obtained by the Wall Street Journal, the January study will last two years and follow 20,000 participants, half of whom are at high risk for dementia.

Articles topics

Apple | behavioral biometrics | biometric sensors | biometrics | expression recognition | health care | iPhone | mobile device

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